Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method, in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a cognitive computing system, the method comprising: receiving, by the personalized training recommendation system, a request from client computing device associated with a user, the request being to generate a personalized training regimen for a specified athletic event occurring at a future time; extracting, by the cognitive computing system, event information comprising at least one of physical features or environmental features of one or more geographical segments of the specified athletic event based on an ingestion, by the cognitive computing system, of first data regarding the specified athletic event and generation, by the cognitive computing system, of a first set of features corresponding to the specified athletic event extracted from the ingested first data; identifying, by the cognitive computing system, based on the event information, geographical region information from a knowledge base, for one or more portions of a geographical region within a specified geographical range of a home location associated with the user, wherein the one or more portions approximate at least one of the physical features or environmental features of the one or more geographical segments associated with the specified athletic event within a predetermined tolerance, wherein the identification of the geographical region information is based on a generation, by the cognitive computing system, of a second set of features, comprising at least one of physical features or environmental features corresponding to the one or more portions of the geographical region, extracted from ingested second data, and a cognitive comparison of the first set of features and the second set of features using machine learning logic that learns weights associated with different types of features through a machine learning process and applies the weights to the different types of features present in the second set of features via one or more functions to score the one or more portions of the geographical region; generating, by the cognitive computing system, a training course at least by combining a selected set of the portions of the geographical region based on an evaluation, by the cognitive computing system, of a level of matching, for each portion of the geographical region in the set of portions, based on the scores associated with the one or more portions of the geographical region generated by the machine learning logic; and transmitting, by the cognitive computing system, the generated training course to the client computing device for presentation to the user as the personalized training regimen for use by the user in preparing for the specified athletic event.
2. The method of claim 1 , wherein the event information includes one or more of a date of the specified athletic event, a location of the specified athletic event, a course map of the specified athletic event, a terrain associated with the course, or historical environmental characteristics associated with the location and the date.
This invention relates to systems and methods for managing and analyzing athletic event data. The technology addresses the challenge of organizing and utilizing detailed information about athletic events to enhance participant preparation, performance tracking, and event planning. The method involves collecting and storing comprehensive event information, which includes key details such as the date, location, and course map of the specified athletic event. Additionally, the system captures terrain data associated with the course, providing insights into the physical challenges participants may encounter. Historical environmental characteristics, such as weather patterns or temperature trends, are also gathered to offer context for training and event conditions. This data is structured to support various applications, including personalized training recommendations, performance analytics, and event logistics optimization. By integrating these elements, the system enables athletes, coaches, and event organizers to make informed decisions based on detailed, location-specific, and time-relevant information. The invention improves the efficiency and accuracy of athletic event management by centralizing and analyzing these critical data points.
3. The method of claim 1 , further comprising: monitoring, by the cognitive computing system via communication with a wearable health or activity monitoring device associated with the user, performance of the user during training on the generated training course to generate performance data; determining, by the cognitive computing system, areas of weakness or insufficient performance by the user on the training course based on an evaluation of the performance data; and correlating, by the cognitive computing system, the areas of weakness or insufficient performance with characteristics of corresponding portions of the training course.
This invention relates to cognitive computing systems for personalized training course generation and performance monitoring. The technology addresses the problem of creating adaptive training programs that dynamically adjust based on user performance, particularly in fields like education, fitness, or professional skill development. The system generates a training course tailored to a user's needs by analyzing their initial performance data and selecting relevant training materials. It then monitors the user's progress during training using data from wearable health or activity monitoring devices. The system evaluates this performance data to identify areas where the user struggles or performs inadequately. By correlating these weaknesses with specific portions of the training course, the system can refine future training content to better address the user's deficiencies. The wearable device data may include metrics like physical exertion, focus levels, or task completion times, depending on the training context. The system's ability to link performance gaps to specific training segments allows for targeted improvements, ensuring more effective learning or skill development. This approach enhances traditional training methods by providing real-time, data-driven adjustments to optimize user outcomes.
4. The method of claim 3 , further comprising: correlating, by the personalized training recommendation system, the areas of weakness or insufficient performance, the characteristics of corresponding portions of the training course, and one or more exercises to be performed on one or more pieces of exercise devices to train the user for those characteristics of the corresponding portions of the training course; and presenting, by the personalized training recommendation system, an output to the user to inform them of the areas of weakness or insufficient performance, the characteristics of the corresponding portions of the training course, and the one or more exercises to be performed.
This invention relates to personalized training recommendation systems designed to improve user performance in specific activities, such as sports or physical training courses. The system identifies areas where a user exhibits weakness or insufficient performance during training. It then analyzes the characteristics of the training course segments where these weaknesses occur. The system correlates these weaknesses with specific exercises that can be performed on exercise devices to address the identified deficiencies. The system generates a personalized training plan that includes these exercises and presents the plan to the user, detailing the areas of weakness, the relevant training course characteristics, and the recommended exercises. This approach ensures targeted improvement by linking performance gaps directly to tailored training activities. The system may also track user progress and adjust recommendations over time to optimize training effectiveness. The goal is to enhance user performance by providing data-driven, customized training guidance.
5. The method of claim 4 , wherein correlating the areas of weakness or insufficient performance, the characteristics of corresponding portions of the training course, and one or more exercises to be performed further comprises: correlating the areas of weakness or insufficient performance with types of motions used at the corresponding portions of the training course; and correlating the types of motions with the one or more exercises to be performed on one or more pieces of exercise devices to train the user.
This invention relates to a system for improving athletic performance by analyzing a user's weaknesses during a training course and recommending targeted exercises. The problem addressed is the lack of personalized training programs that adapt to an athlete's specific areas of weakness or insufficient performance during a training course. The system identifies these weaknesses by analyzing the user's performance data at different portions of the training course. It then correlates these weaknesses with the types of motions required at those portions. Based on this correlation, the system recommends specific exercises to be performed on exercise devices, such as treadmills, rowing machines, or weight machines, to strengthen the user's performance in those areas. The exercises are designed to mimic or counteract the motions where the user struggled, ensuring targeted improvement. This approach provides a more efficient and effective training regimen by directly addressing performance gaps with tailored exercises. The system enhances athletic training by bridging the gap between general fitness routines and personalized performance optimization.
6. The method of claim 3 , further comprising: modifying, by the personalized training recommendation system, the training course to include one or more other portions of the geographical region, not previously in the set of portions, based on the correlation of areas of weakness or insufficient performance with characteristics of corresponding portions of the training course, to thereby generate a modified training course.
A personalized training recommendation system enhances training courses by dynamically adjusting content based on performance data. The system identifies areas of weakness or insufficient performance in a user's training progress and correlates these with specific portions of a geographical region covered in the training course. By analyzing these correlations, the system modifies the training course to include additional portions of the geographical region that were not previously part of the training material. This modification ensures that the training course addresses the identified weaknesses, improving overall performance. The system may also generate a modified training course that incorporates these new portions, providing a more targeted and effective learning experience. The approach leverages performance data to dynamically adapt training content, ensuring that users receive personalized instruction tailored to their specific needs. This method improves training efficiency by focusing on areas where improvement is most needed, thereby optimizing learning outcomes.
7. The method of claim 6 , wherein the one or more other portions are one or more other portions that have at least one similar characteristic to the characteristics of the corresponding portions of the training course for which the user has shown a weakness or insufficient performance.
This invention relates to adaptive learning systems that identify and address user weaknesses in training courses. The method involves analyzing a user's performance in a training course to detect portions where the user has shown weaknesses or insufficient performance. The system then identifies one or more other portions of the training material that share at least one similar characteristic with the problematic portions. These similar portions are selected for additional focus, such as through targeted review, practice exercises, or remedial content. The goal is to improve learning efficiency by reinforcing areas where the user struggles while leveraging similarities in the training material to optimize the learning process. The method may involve comparing characteristics such as subject matter, difficulty level, or conceptual relationships to determine which portions are most relevant for targeted intervention. This approach ensures that the user receives personalized support tailored to their specific learning gaps, enhancing overall comprehension and retention.
8. The method of claim 6 , wherein modifying the training course further comprises modifying the training course to include other portions of the geographical region, not previously in the set of portions, and which do not match characteristics of the one or more geographical segments of the specified athletic event, but have at least one of physical features or environmental features that will assist the user in strengthening their performance with regard to the identified areas of weakness or insufficient performance.
This invention relates to adaptive training course modification for athletic performance improvement. The method addresses the challenge of optimizing training by dynamically adjusting course segments to target specific weaknesses in an athlete's performance. The system identifies areas where an athlete underperforms, such as endurance, speed, or technique, and modifies the training course to include new geographical portions that do not necessarily match the characteristics of the athlete's target event but contain physical or environmental features designed to strengthen those weaknesses. For example, if an athlete struggles with uphill endurance, the system may add steep terrain or high-altitude segments to the course, even if the target event does not include such terrain. The modifications are based on analyzing the athlete's performance data and selecting segments that introduce controlled challenges to improve specific skills. This approach ensures that training is tailored to the athlete's needs, enhancing overall performance by systematically addressing deficiencies through targeted environmental and physical adaptations.
9. The method of claim 1 , wherein generating the training course comprises concatenating the selected set of portions with other non-selected intervening portions between selected portions to form a contiguous training course.
This invention relates to a method for generating a training course from a set of video segments. The problem addressed is the need to create a coherent and contiguous training course by selecting relevant portions of video content while maintaining logical flow between segments. The method involves selecting a set of portions from a video source, where each portion is a segment of the video that contains training-relevant content. These selected portions are then concatenated with non-selected intervening portions that lie between the selected segments. The intervening portions serve to maintain continuity and context between the selected training segments, ensuring the final training course is coherent and logically structured. The concatenation process combines the selected and intervening portions into a single, contiguous training course without gaps or abrupt transitions. This approach allows for the creation of a structured training course from raw video content by preserving the natural flow of information while focusing on the most relevant training material. The method ensures that the training course remains understandable and engaging by including necessary transitional content between key segments.
10. The method of claim 1 , wherein transmitting the generated training course to the client computing device for presentation to the user as the personalized training regimen for use by the user in preparing for the specified athletic event comprises transmitting data defining the training course to a wearable health or activity monitoring device associated with the user.
This invention relates to personalized athletic training systems that adapt to a user's physiological and performance data. The system generates a customized training regimen for a specified athletic event by analyzing the user's historical performance data, physiological metrics, and environmental conditions. The training regimen is dynamically adjusted based on real-time feedback from wearable health or activity monitoring devices, such as smartwatches or fitness trackers, to optimize training effectiveness. The system collects data from the wearable device, including heart rate, movement patterns, and other biometric measurements, to assess the user's current fitness level and progress. Using machine learning algorithms, the system identifies patterns in the data to tailor the training course, adjusting intensity, duration, and exercise types to align with the user's goals and capabilities. The training course is then transmitted to the wearable device, which guides the user through the regimen, providing real-time feedback and adjustments during workouts. This approach ensures that the training is personalized, adaptive, and optimized for the user's specific needs, improving performance and reducing injury risk. The integration with wearable devices allows for seamless tracking and real-time modifications, enhancing the overall training experience.
11. The method of claim 1 , wherein the request specifies a temporal criterion for the specified athletic event, and wherein a cognitive computing system performs a cognitive computing analysis of a corpus of information to predict at least one of physical features or environmental characteristics of the specified athletic event corresponding to the temporal criterion specified in the request.
This invention relates to cognitive computing systems for analyzing athletic events based on temporal criteria. The method involves receiving a request that specifies a temporal criterion for a particular athletic event, such as a date, time, or time range. A cognitive computing system then performs an analysis of a corpus of information to predict physical features or environmental characteristics of the event that correspond to the specified temporal criterion. The physical features may include athlete performance metrics, equipment specifications, or physiological data, while environmental characteristics may include weather conditions, terrain details, or other external factors. The system processes the corpus of information, which may include historical data, real-time data, or simulated scenarios, to generate predictions that help users understand or prepare for the event. The analysis may involve machine learning, natural language processing, or other cognitive computing techniques to extract relevant insights from the data. This approach enables users to anticipate conditions or outcomes based on temporal factors, improving decision-making in athletic contexts.
Unknown
September 1, 2020
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